Inflammatory Status in Moderate and Severe COPD Patients: What Are the Related Factors?
Notice bibliographique
Résumé
Background: Systemic inflammation is believed to have an important role in pathogenesis of Chronic Obstructive Pulmonary Disease (COPD) and its related factors should be considered in monitoring of the disease. In the current study, possible link between inflammatory status and various related factors in patients with COPD was assessed. Method: Sixty-one COPD patients according to the inclusion criteria participated in this study. For assessing nutritional status, SGA (subjective global assessment) and 24-hour dietary recall method were used and Health-related quality of life (HRQoL) was assessed by St. George’s respiratory questionnaire (SGRQ), instrumental activities of daily living scales (IADLs), and Katz Index. Moreover, Anthropometric and body composition measurements including weight, height, BMI, FFM, and FFMI were measured by standard methods and BIA. Additionally, muscle strength was assessed using a hydraulic hand dynamometer. Finally, blood samples were collected to assess biochemical factors including TNF-α, IL-6, MDA, vitamin C, magnesium, and Glutathione. Stepwise model was performed for evaluating the relationship between inflammatory markers (TNF-α and IL-6) and associated markers mentioned above. Characteristics of participants were expressed in percentage and mean ±SD and analyzed by SPSS software. Results: The results of the current study showed that the intake of PUFA and vegetables, plasma vitamin C and serum MDA could possibly affect inflammation according to IL-6 and TNF- α concentrations. On the other hand, systemic inflammation (IL-6 and TNF-) aggravated mean right and left handgrip strength, Katz index and nutritional status (SGA score) significantly (P <0.05). Conclusion: To sum up, our results confirmed the inter-relationship between inflammatory markers and intake of some dietary components, oxidative stress biomarkers, muscle function, and nutritional status in COPD patients. These factors might affect over each other and further studies are needed to better elucidate this issue. Background: Systemic inflammation is believed to have an important role in pathogenesis of Chronic Obstructive Pulmonary Disease (COPD) and its related factors should be considered in monitoring of the disease. In the current study, possible link between inflammatory status and various related factors in patients with COPD was assessed. Method: Sixty-one COPD patients according to the inclusion criteria participated in this study. For assessing nutritional status, SGA (subjective global assessment) and 24-hour dietary recall method were used and Health-related quality of life (HRQoL) was assessed by St. George’s respiratory questionnaire (SGRQ), instrumental activities of daily living scales (IADLs), and Katz Index. Moreover, Anthropometric and body composition measurements including weight, height, BMI, FFM, and FFMI were measured by standard methods and BIA. Additionally, muscle strength was assessed using a hydraulic hand dynamometer. Finally, blood samples were collected to assess biochemical factors including TNF-α, IL-6, MDA, vitamin C, magnesium, and Glutathione. Stepwise model was performed for evaluating the relationship between inflammatory markers (TNF-α and IL-6) and associated markers mentioned above. Characteristics of participants were expressed in percentage and mean ±SD and analyzed by SPSS software. Results: The results of the current study showed that the intake of PUFA and vegetables, plasma vitamin C and serum MDA could possibly affect inflammation according to IL-6 and TNF- α concentrations. On the other hand, systemic inflammation (IL-6 and TNF-) aggravated mean right and left handgrip strength, Katz index and nutritional status (SGA score) significantly (P <0.05). Conclusion: To sum up, our results confirmed the inter-relationship between inflammatory markers and intake of some dietary components, oxidative stress biomarkers, muscle function, and nutritional status in COPD patients. These factors might affect over each other and further studies are needed to better elucidate this issue.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».